The Biostatistics and Modeling Core provides a centralized plan for experimental design, data integration and predictive modeling of research data that is utilized by all of our Research Projects and Cores. We have created a multi-disciplinary team with expertise in statistics, bioinformatics, modeling and computer science to provide broad support capabilities in this Research Support Core. In the first three years of this SRP, Core C has provided invaluable support in all aspects of the research. From experimental design to multivariate integration, from bioinformatics to regulatory networks, and from data management to customized software solutions, our Core has facilitated scientific advancement in the research projects and enabled data integration across multiple research projects. In the next five years, we propose to continue our support of the program, providing sophisticated data analyses and expand our efforts into more predictive, computational modeling through three primary specific aims; 1) biostatistics support to facilitate linkage of exposure (source) to phenotype (outcome) for chemical mixtures, 2) predictive modeling and informatics for mechanistic evaluation of mixtures, and 3) customized software solutions for data processing and integrations. Core C ensures statistically robust experimental design, standardized data pipelines, data integration and results interpretation across all research projects and cores to ensure robust measurement of exposure, dose, response and phenotype and achieve source to outcome linkage for science-based risk assessment. Multidisciplinary training of toxicology students and postdoctoral fellows in statistics and bioinformatics also assures that the next generation of researchers and professionals tasked with protecting human health and the environment from the risks of hazardous substances will possess the skills to analyze and interpret their own data.